one of the Method for Identify Urban Distressed Areas is GIS Method, which that we Used some Layer for this Purpose and Finally the Urban Distressed Areas will be Identified. but for my research, I Wanna Identify Urban Distressed Areas by Image Satellite (for Example LANDSAT). How I Can Do it?
Hi Behrouz,
first thing to do when approaching a remote sensing problem (or when asking for help) is always to define very clearly what you want to find out. What is a "distressed" area. Maybe in your mind it's clear, but in English it's ambiguous. You could be talking about an area affected by a disasters (in which case urban structural damage would be of interest). But distress can also relate to other factors, such as poverty, social unrest, etc.
You need to very very clear about the aims of the investigation, only then can you define the specific characteristics for damage, poverty, etc. And only then can you decide what images and information extraction methods will be suitable. Landsat will likely be too coarse for most urban studies.
Regards, Norman
Hi Behrouz,
first thing to do when approaching a remote sensing problem (or when asking for help) is always to define very clearly what you want to find out. What is a "distressed" area. Maybe in your mind it's clear, but in English it's ambiguous. You could be talking about an area affected by a disasters (in which case urban structural damage would be of interest). But distress can also relate to other factors, such as poverty, social unrest, etc.
You need to very very clear about the aims of the investigation, only then can you define the specific characteristics for damage, poverty, etc. And only then can you decide what images and information extraction methods will be suitable. Landsat will likely be too coarse for most urban studies.
Regards, Norman
HI Norman
my means is that ectract the urban distressed In terms of age, form, size and shape of structures (buildings). one of the methods that used for this issue is object-base classification, i wanna find more methods for this issue.
thank you so much
Hi Behrouz,
totally agree with Norman about 'defining', you may make use of ESA's Earth Observation Programme 'Sentinel-1A' (April 2014) aka COPERNICUS by the EC. http://www.esa.int/Our_Activities/Observing_the_Earth/How_to_get_Earth_observation_data
Data access and usage are open worldwide to everybody. Please find as well former papers (partly including your issue) published under GMES (Global Monitoring on Environment and Security - the predecessor of Copernicus). Find pdf-downloads about GMES studies on the web. Contains various approaches, different methods and direct contact to authors and scientific researchers.
Hope this helps
HO
Hi Behrouz,
you write "my means is that ectract the urban distressed In terms of age, form, size and shape of structures (buildings)". To me it seems that you are talking about structural/urban decay - a term that has a very differnet meaning from distress. I suggest looking at literature about urban morphology, detection of deprived areas/slums, which has been done with spatial metrics (e.g. FRAGSTATS, see work by people like Martin Herold (start wtih older papers to get the basics, such as Herold, M., Liu, X. H., & Clarke, K. C. (2003). Spatial metrics and image texture for mapping urban land use. Photogrammetric Engineering and Remote Sensing, 69(9), 991-1001). Later there was quite some work on slum mapping, including witht eh sue of ontologies and object-based iamge analsyis (e.g., Kohli, D., Sliuzas, R., Kerle, N., & Stein, A. (2012). An ontology of slums for image-based classification. Computers Environment and Urban Systems, 36(2), 154-163. doi: 10.1016/j.compenvurbsys.2011.11.001). Keep in mind that there are also a lot of civil or structural engineers who are lookign at decay at a very local scale, such as signs of wear or instability of bridges and such infrastructure. The spatial scale then is of course very different, and the data used are very local (e.g., images taken by drones/ UAV). In my group we have used such data also for structural damage mapping, e.g., down to finding small cracks on house facades (e.g., Fernandez Galarreta, J., Kerle, N., & Gerke, M. (2015). UAV-based urban structural damage assessment using object-based image analysis and semantic reasoning. Natural Hazards and Earth System Sciences, 15(6), 1087-1101. doi: 10.5194/nhess-15-1087-2015).
Good luck, Norman
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